International Journal of Wireless Communications and Mobile Computing 2015; 3(5): 46-50 Published online August 31, 2015 (http://www.sciencepublishinggroup.com/j/wcmc) doi: 10.11648/j.wcmc.20150305.11 ISSN: 2330-1007 (Print); ISSN: 2330-1015 (Online)

Hands-on Analysis of 802.11ac Modulation and Coding Scheme

Doru Gabriel Balan, Alin Dan Potorac, Radu Cezar Tărăbuță

Ștefan cel Mare University of Suceava / Computers, Electronics and Automation Department, Suceava, Romania

Email address: dorub@usv.ro (D. G. Balan), alinp@eed.usv.ro (A. D. Potorac), radut@stud.usv.ro (R. C. Tărăbuță)

To cite this article: Doru Gabriel Balan, Alin Dan Potorac, Radu Cezar Tărăbuță. Hands-on Analysis of 802.11AC Modulation and Coding Scheme. International

Journal of Wireless Communications and Mobile Computing. Vol. 3, No. 5, 2015, pp. 46-50. doi: 10.11648/j.wcmc.20150305.11

Abstract: Current communication networks are full of mobile devices that are capable of performing data transfers at high

data rates or access high resolution video streams. For such requirements, in the data communications there is a permanent

concern of wireless communications development to keep up with the wired communication networks. Because the 802.11n

technology is not fast enough for increasingly more users willing games and online broadcasts, the 802.11ac technology was

developed. This new IEEE standard, along with the future technology 802.11ad, is aiming to achieve a new level of performance,

called VHT (Very High Throughput). The goal is to reach transfer rates (over 1Gbps for now) comparable to those establish in

wired networks. This article is proposing a study over 802.11ac technology by exploring the performances of the specific MCS

(Modulation and Coding Scheme) with a handy digitally modulated signals investigation method, CCDF (Complementary

Cumulative Distribution Function).

Keywords: Wireless, 802.11ac, Modulation, Coding Scheme

1. Introduction

IEEE 802.11ac [1] is one of the ongoing WLAN standards

aiming to support very high throughput (VHT) with data rate

of up to 6 Gbps below the 6GHz band. [2].

The increasing demands on modern Wi-Fi networks are

based on several trends that are requiring ever greater levels

of performance, scalability, and availability [3]:

� Proliferation of mobile devices (devices as smartphones

and tablets rely exclusively on Wi-Fi for network

connectivity);

� Multiple devices per user (most users are using

concurrently multiple devices with networking

capabilities.);

� Always-on connectivity (it is common that today users

have permanent connectivity to the Internet);

� Wi-Fi as the primary network access method;

� IoT (Internet of Things), IoE (Internet of Everything)

and BYOD (Bring Your Own Device) expansion;

� Cellular network offload (3G, 4G and future 5G network

protocols are avoiding network congestion);

� Hotspots are becoming increasingly more important.

� The theoretical maximum data rate and actual user

throughput, that will be lower due to the shared medium,

and transmission, management and control overhead,

depend on a number of factors, such as:

� Physical-layer (PHY) connection rates;

� Number of spatial streams;

� Allocated channel width;

� Modulation and coding scheme (MCS) used;

� Guard interval (time between transmitted characters).

2. Wireless Technology Elements

2.1. 802.11ac Characteristics

From this perspective, several characteristics of 802.11ac

technology can be easily identified [4, 5], such as:

� Introduces the new VHT operating mode, that is a mixt

mode, supporting 802.11a and 802.11n clients in the

5Ghz band;

� Supports from 1 to 8 (up to 4 per client) spatial streams

between infrastructure access points and wireless

clients, using several principles, like:

� Space multiplexing (signal is splinted in multiple

signal streams, each transmitted in a separate spatial

stream),

� Space Time Block Coding - STBC (uses more

antennas to redundantly transmit a single traffic

47 Doru Gabriel Balan et al.: Hands-on Analysis of 802.11AC Modulation and Coding Scheme

stream over multiple RF paths),

� Multi-User Multiple Input Output (MU-MIMO) use

a multiple antenna array to direct beams and transmit

simultaneously to multiple clients.

� Wider RF transmission channels, it adds 80MHz and

160MHz channels to the 5GHz band;

� Higher Modulation and Coding Schemes (MCS),

introducing the 256 QAM signal modulation;

� Specifies 10 MCS indices (0-9, as in Figure 1);

When all specified enhancements are enabled, 802.11ac

delivers a maximum PHY data rate of 6933 Mbps, as can be

seen in Figure 1, in the last filled cell.

2.2. Specific MCS - Modulation and Coding Scheme

As seen before, network communications via 802.11ac can

be realized using one of the 10 MCS provided with maximum

8 spatial streams. Figure 1 is presenting the 802.11ac

characteristics, regarding PHY data rates and MCS, for only

two situations of user number of spatial streams, namely for 1

spatial stream and for 8 spatial streams. Obviously there are

also data for the other cases, (the cases with 2-7 spatial

streams), which were excluded from organizing

considerations.

Figure 1. 802.11ac PHY data rates for 1 and 8 spatial streams [3].

Figure 2 shows the current state of technology

development 802.11ac identified by the initially developed

set of 802.11ac equipment (802.11ac 1st wave). As can be

seen, the actual data rate is 1300 Mbps.

In the results included in this article we have concentrated

over 802.11ac specific Modulation and Coding Schemes

(MCS). Our determinations are based on the CCDF

(Complementary Cumulative Distribution Function)

investigation method.

Figure 2. 802.11 PHY data rates in real use [6].

3. Investigation Method

Measurement of the CCDF is often used for evaluating

nonlinearities of amplifiers or transmitter output stages, for

instance. This measurement indicates how often the

observed signal reaches or exceeds a specific level. From a

physical point of view, the CCDF measurement is the

integral of the distribution function versus the level

(integration of the observed level to infinity).

Comparison of evaluated or measured values and

theoretical reference values (as CCDF Gaussian), as it can be

seen in Figures 5-14, quickly yields information on the

nonlinear response of all types of active elements. However,

the great advantage of the CCDF measurement is that the

useful signal itself is analyzed; as a result, it is not necessary

to transmit complex test sequences. CCDF determination is a

very important measurement in RF transmission systems.

Measuring the CCDF is a simple and effective method of

determining the nonlinear characteristics of active elements.

[6].

4. Testbed Elements

To achieve the aimed performance analysis on 802.11ac

modulation and coding scheme, it was used a testing space

consisting of a Keysight (formerly Agilent) set of tools.

There are two key elements of the test bench that provided

the results presented in this paper:

The first element (software) is the N7617B Signal Studio

for WLAN 802.11a/b/g/n/ac [7], used to design the 802.11ac

signals;

The second element (hardware) is a vector signal

generator, N5182A MXG [8], with N7617B option, for

testing loaded signals from software.

The interconnection of these components, as in Figure 3,

allows controlling the theoretical elements for 802.11ac

technology-specific signals description and the signal

characteristics validation, achieved through vector signal

generator.

International Journal of Wireless Communications and Mobile Computing 2015; 3(5): 46-50 48

Figure 3. Component test configuration [9].

5. Mathematics Behind

As mentioned in mathematical theories, expressed by [10]

and [11], in probability theory and statistics, the cumulative

distribution function (CDF), or just distribution function,

describes the probability that a real-valued random variable

X with a given probability distribution will be found to have a

value less than or equal to x . In the case of a continuous

distribution, it gives the area under the probability density

function from minus infinity to x . Cumulative distribution

functions are also used to specify the distribution of

multivariate random variables.

The cumulative distribution function of a real-valued

random variable X is the function given by (1):

( ) ( )XF x P X x= ≤ (1)

where the right-hand side represents the probability that the random variableX takes on a value less than or equal to x .

The probability that X lies in the semi-closed interval( , ]a b ,

wherea b< , is expressed by (2):

( ) ( ) ( )X X

P a X b F b F a< ≤ = − (2)

The CDF of a continuous random variable X can be

expressed as the integral of its probability density function

Xf as in (3):

( ) ( )x

X XF x f t dt

−∞

= ∫ (3)

In the case of a random variableX which has distribution

having a discrete component at a valueb , stated by (4),

( ) ( ) lim ( )X X

x b

P X b F b F x−→

= = − (4)

If XF is continuous atb , this equals zero and there is no

discrete component atb .

Sometimes, it is useful to study the opposite question and

ask how often the random variable is above a particular level.

This is called the Complementary Cumulative Distribution

Function (CCDF) or simply the tail distribution or

exceedance, and is defined as in (5):

( ) ( ) 1 ( )F x P X b F x= > = − (5)

This has applications in statistical hypothesis testing, for

example, because the one-sided p-value is the probability of

observing a test statistic at least as extreme as the one observed. Thus, provided that the test statistic, T has a

continuous distribution, the one-sided p-value is simply given

by the CCDF, for an observed value t of the test statistic will

be expressed by (6):

( ) ( ) 1 ( )T

p P T t P T t F t= ≥ = > = − (6)

In survival analysis, ( )F x is called the survival function

and denoted ( )S x , while the term reliability function is

common in engineering.

6. Practical Determinations

The objective of practical determinations involves passing

the generated signal through all 802.11ac available MCS. The

analysis result is the digitally modulated signals characteristics

identification, based on CCDF curves observation for each

generated signal. Figure 4 shows the spectrum analysis diagram

for a sample 802.11ac signal.

Figure 4. Signal spectrum MCS 0-9.

49 Doru Gabriel Balan et al.: Hands-on Analysis of 802.11AC Modulation and Coding Scheme

7. Results

Diagrams from Figures 5-14 are providing an intuitive

analysis of 802.11ac signals, for each specific MCS, emerged

from the use of CCDF analysis functions over entire signal or

only the burst part of the signal. The analysis is made by

comparing the signal power with the Gaussian CCDF

reference line (red line on Figs. 5-14).

To select the portion of the waveform to calculate the CCDF

data the analysis charts are containing the both components

available on signal design operations (Waveform CCDF and

Burst CCDF, green and blue lines). Waveform CCDF will

include all components of the configured frame including gaps

and non-transmitted portions (both RF burst on and off

portions). Burst CCDF will include the configured bursts only

(this does not includes gaps or times when the RF burst is off).

Figure 5. CCDF analysis for MCS 0.

Figure 6. CCDF analysis for MCS 1.

Figure 7. CCDF analysis for MCS 2.

Figure 8. CCDF analysis for MCS 3.

Figure 9. CCDF analysis for MCS 4.

Figure 10. CCDF analysis for MCS 5.

Figure 11. CCDF analysis for MCS 6.

International Journal of Wireless Communications and Mobile Computing 2015; 3(5): 46-50 50

Figure 12. CCDF analysis for MCS 7.

Figure 13. CCDF analysis for MCS 8.

Figure 14. CCDF analysis for MCS 9.

8. Conclusions

It is well known that the modulation format of a signal affects

its power characteristics. Using CCDF curves, we can fully

characterize the power statistics of different modulation formats,

and compare the results of choosing one modulation format

over another.

The determinations contained in this article are guided on the

behavior of radio signals in the technology 802.11ac. The

outcomes obtained and presented in this paper can be used as a

good base for identifying 802.11ac characteristics. The analysis

of MCS through CCDF gives valuable information about signal

levels on each available MCS on 802.11ac, taking as

comparative reference the band-limited Gaussian noise

reference curve.

The results presented in this study are presenting the

exploration step that is a part of a started and more ample

research initiative regarding wireless interference detection and

prevention. Future operations are aiming the analysis of the

crowded signal spectrum, faced by the wireless

communications and the opportunities offered by 802.11ac

technology to solve such problems, regarding the benefits of

using multiple antenna techniques.

Acknowledgements

This paper has been financially supported within the project

entitled „SOCERT. Knowledge society, dynamism through

research”, contract number POSDRU/159/1.5/S/132406. This

project is co-financed by European Social Fund through

Sectoral Operational Programme for Human Resources

Development 2007-2013. Investing in people!

References

[1] IEEE 802.11ac, http://www.ieee802.org/11/Reports/tgac/update.htm.

[2] Verma, L.; Fakharzadeh, M.; Sunghyun Choi, "Wifi on steroids: 802.11AC and 802.11AD," Wireless Communications, IEEE, vol.20, no.6, pp.30, 35, December 2013.

[3] Andrew von Nagy, "Aerohive High-Density Wi-Fi Design & Configuration Guide v2 ", Aerohive Networks, 2013.

[4] Eng Hwee Ong; Kneckt, J.; Alanen, O.; Zheng Chang; Huovinen, T.; Nihtila, T., "IEEE 802.11ac: Enhancements for very high throughput WLANs," Personal Indoor and Mobile Radio Communications (PIMRC), 2011 IEEE 22nd International Symposium on, vol., no., pp.849,853, 11-14 Sept. 2011.

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[7] N7617B Signal Studio for WLAN 802.11a/b/g/n/ac, http://www.keysight.com/en/pd-803256-pn-N7617B/signal-studio-for-wlan-80211a-b-g-n-ac?cc=US&lc=eng.

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[9] Agilent Technologies,, Signal Studio for WLAN 802.11a/b/g/n/ac - N7617B, Technical Overview 5990-9008EN, January 16, 2014.

[10] Cumulative distribution function, http://en.wikipedia.org/wiki/Cumulative_distribution_function

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